The androgen receptor (AR) signaling axis remains the dominant therapeutic target in prostate cancer treatment, however the diversity of patient outcomes suggests alternate transcription factors (TFs) may contribute to aggressive prostate cancer biology and impact treatment response. To resolve their relative contribution in silico, we quantified the transcriptional ‘identity’ of prostate cancer subtypes within a discovery cohort of aggressive and therapy-resistant prostate tumor xenografts (PDX). Using a proven cell-reprogramming framework1-3, we applied comparative network-based modelling of non-malignant and malignant prostate epithelial transcriptomes to define genome-wide signaling circuitry and prioritize TFs most associated with aggressive prostate cancer lineage. Importantly, clinical validation of a discovery set of TF-network signatures revealed strong associations with patient prognosis and treatment-resistance when detected in the primary prostate tumor of patients enrolled on the CHAARTED phase 3 trial, indicating a role in driving patient outcomes. Knockdown of selected master TFs strongly inhibited the growth of patient-derived prostate cancer organoids, indicating relevant cancer-dependency genes. As proof-of-concept, we leveraged unbiased systems pharmacology to match drug compounds against core TF-networks predicted within our framework. Strong anti-cancer activity was observed following treatment of PDX-organoids with predicted drug compounds, but not control drugs, which we show effectively targeted core TF-networks at the transcriptional level. Collectively, our approach simplifies complex networks to prioritize key TFs driving aggressive prostate cancer lineage and reveals potential new therapeutic targets, beyond the AR.